AI Strategy & Systems

Your AI initiative deserves someone who builds, not just advises.

Most organizations have the vision. What stalls them is translation — turning strategy into something that actually runs. I've spent the last two years inside an enterprise AI lab doing exactly that.

Connect on LinkedIn → See the work
Abstract scribble illustration

Every system starts as a scribble.

19
Prototypes built in year one
480×
Faster innovation cycles
$933M
Opportunity identified
3
Prototypes advanced to MVP
The Real Problem

AI pilots don't fail because the technology fails.

They fail because nobody built the system around them. No intake process. No validation loop. No feedback mechanism. Just a proof of concept that impresses in the demo and disappears before it scales.

The gap isn't talent or budget. It's translation — between what leadership wants AI to do and what the organization is actually structured to deliver.

Most AI leaders can tell you what needs to happen. Fewer can build the infrastructure that makes it happen repeatedly — and hand it off to a team that keeps it running after they've moved on to the next problem.

That's the specific thing I do.

Translation Between — 3D grid showing Vision, Ambition, and Execution axes
How I Work

From ambiguous to operational — in sprints, not quarters.

I've run this inside a real enterprise environment, under real constraints, with real stakeholders. Here's the pattern that works.

01
Diagnose the real gap

Not the AI gap — the organizational gap. Where does strategy break down before it reaches execution? What's the actual bottleneck between vision and working prototype?

02
Design the system, build the proof

Intake process, validation loop, governance model — then a working prototype that proves the concept isn't theoretical. Strategy that stays in a deck is just a pitch.

03
Hand off something that runs without me

The operating model, the documentation, the team habits. I measure success by whether the system compounds after I'm no longer the one running it.

Intelligence → Alignment → Innovation → Measurable Business Value
Selected Work

These aren't hypotheticals.

Each project ran inside a real organization with real constraints. The outcomes are measured, not projected.

AI Systems
Building an AI Lab That Could Run Without Me
Designed the intake, validation, and sprint system that turned scattered AI ideas into a repeatable innovation engine — 19 prototypes in year one.
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AI Systems
When Skeptical Partners Watched the System Work Live
A multi-agent pipeline that compressed months of innovation discovery into hours — 23 validated opportunities, $933M in mapped value, demoed live.
Read case study
AI Products
Making Static Research Answer Questions It Was Never Asked
Built a behavioral simulation platform — context classifier, semantic retrieval over 598 grounded Q&A pairs, persona-grounded generation — that turned shelved research into a queryable tool.
Read case study
AI Operations
Running 18 Projects Without Losing a Thread
An AI operating system that tracks a full portfolio, captures performance evidence continuously, and cut weekly synthesis time 70%.
Read case study
Go-to-Market
Narrative at Scale: AI-Driven GTM for a Tax Data Platform
Sole-contributor, end-to-end: a narrative-driven, AI-assisted GTM framework combining storytelling psychology with synthetic video production.
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Go-to-Market
Thought Leadership as Discovery: AI-Augmented Workshops
A Value Lab workshop format that turns a 3.5-hour session into five AI-synthesized deliverables within 48 hours — designed to scale across cities.
Read case study
About

I've always taught myself the next thing before it was obvious.

Design before clients knew they needed design-first thinking. Brand strategy before most agencies had a strategy practice. AI systems before most organizations knew they needed to care.

That pattern — dive in, read everything, run experiments, build something useful — is the same one that produced 19 prototypes and $933M in validated opportunity inside an enterprise AI lab in year one.

I've built two agencies from scratch, served as Chief Strategy Officer through a $4M acquisition, and spent the last two years designing the infrastructure that makes AI innovation repeatable rather than heroic.

I'm at my best when the problem is ambiguous and the path isn't clear.

Experience

Education & Certifications

2024
Artificial Creativity Certificate & AI Specialization
Parsons School of Design — New York, NY
2024
Strategic Artificial Intelligence Program & AI Advisor
Cornerstone University — Grand Rapids, MI
2023
Business Strategy Specialization
UVA Darden School of Business
2022
JTBD-ODI Fundamentals
Strategyn
2020
Design Strategy / UX-UI / Systems Design Thinking
University of Sydney · CalArts · Cornell University
2004
B.S. Marketing
Virginia Commonwealth University — Richmond, VA

Let's talk about what you're building.

If your organization is serious about moving AI from experiment to infrastructure — and you need someone who's done it before — I'd like to hear about the problem.

Message me on LinkedIn →